High-throughput and sensitive quantitation of plasma catecholamines by ultraperformance liquid chromatography-tandem mass spectrometry using a solid phase microwell extraction plate.

Plasma catecholamines provide a reliable biomarker of sympathetic activity. The low circulating concentrations of catecholamines and analytical interferences require tedious sample preparation and long chromatographic runs to ensure their accurate quantification by HPLC with electrochemical detection. Published or commercially available methods relying on solid phase extraction technology lack sensitivity or require derivatization of catecholamine by hazardous reagents prior to tandem mass spectrometry (MS) analysis. Here, we manufactured a novel 96-well microplate device specifically designed to extract plasma catecholamines prior to their quantification by a new and highly sensitive ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method. Processing time, which included sample purification on activated aluminum oxide and elution, is less than 1 h per 96-well microplate. The UPLC-MS/MS analysis run time is 2.0 min per sample. This UPLC-MS/MS method does not require a derivatization step, reduces the turnaround time by 10-fold compared to conventional methods used for routine application, and allows catecholamine quantification in reduced plasma sample volumes (50-250 μL, e.g., from children and mice).

Fingermark Detection on Thermal Papers: Proposition of an Updated Processing Sequence

The detection of latent fingermarks on thermal papers proves to be particularly challenging because the application of conventional detection techniques may turn the sample dark grey or black, thus preventing the observation of fingermarks. Various approaches aiming at avoiding or solving this problem have been suggested. However, in view of the many propositions available in the literature, it gets difficult to choose the most advantageous method and to decide which processing sequence should be followed when dealing with a thermal paper. In this study, 19 detection techniques adapted to the processing of thermal papers were assessed individually and then were compared to each other. An updated processing sequence, assessed through a pseudo-operational test, is suggested.

Techniques for CT and MR, post-processing, radiation

Brain perfusion can be assessed by CT and MR. For CT, two major techniques are used. First, Xenon CT is an equilibrium technique based on a freely diffusible tracer. First pass of iodinated contrast injected intravenously is a second method, more widely available. Both methods are proven to be robust and quantitative, thanks to the linear relationship between contrast concentration and x-ray attenuation. For the CT methods, concern regarding x-ray doses delivered to the patients need to be addressed. MR is also able to assess brain perfusion using the first pass of gadolinium based contrast agent injected intravenously. This method has to be considered as a semi-quantitative because of the non linear relationship between contrast concentration and MR signal changes. Arterial spin labeling is another MR method assessing brain perfusion without injection of contrast. In such case, the blood flow in the carotids is magnetically labelled by an external radiofrequency pulse and observed during its first pass through the brain. Each of this various CT and MR techniques have advantages and limits that will be illustrated and summarized.Learning Objectives:1. To understand and compare the different techniques for brain perfusion imaging.2. To learn about the methods of acquisition and post-processing of brain perfusion by first pass of contrast agent for CT and MR.3. To learn about non contrast MR methods (arterial spin labelling).

Representing diffusion MRI in 5D for segmentation of white matter tracts with a level set method.

We present a method for segmenting white matter tracts from high angular resolution diffusion MR. images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the position-orientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.

Development of a cost-effective method for platelet-rich plasma (PRP) preparation for topical wound healing.

Platelet-rich plasma (PRP) is a volume of plasma fraction of autologous blood having platelet concentrations above baseline whole-blood values due to processing and concentration. PRP is used in various surgical fields to enhance soft-tissue and bone healing by delivering supra-physiological concentrations of autologous platelets at the site of tissue damage. These preparations may provide a good cellular source of various growth factors and cytokines, and modulate tissue response to injury. Common clinically available materials for blood preparations combined with a two-step centrifugation protocol at 280g each, to ensure cellular component integrity, provided platelet preparations which were concentrated 2-3 fold over total blood values. Costs were shown to be lower than those of other methods which require specific equipment and high-cost disposables, while safety and traceability can be increased. PRP can be used for the treatment of wounds of all types including burns and also of split-thickness skin graft donor sites, which are frequently used in burn management. The procedure can be standardized and is easy to adapt in clinical settings with minimal infrastructure, thus enabling large numbers of patients to benefit from a form of cellular therapy.

In vivo characterisation of a novel water-soluble Cyclosporine A prodrug for the treatment of dry eye disease.

Cyclosporine A (CsA) has been demonstrated to be effective for the treatment of a variety of ophthalmological conditions, including ocular surface disorders such as the dry eye disease (DED). Since CsA is characterised by its low water solubility, the development of a topical ophthalmic formulation represents an interesting pharmaceutical question. In the present study, two different strategies to address this challenge were studied and compared: (i) a water-soluble CsA prodrug formulated within an aqueous solution and (ii) a CsA oil-in-water emulsion (Restasis, Allergan Inc., Irvine, CA). First, the prodrug formulation was shown to have an excellent ocular tolerance as well as no influence on the basal tear production; maintaining the ocular surface properties remained unchanged. Then, in order to allow in vivo investigations, a specific analytical method based on ultra high pressure liquid chromatography coupled with triple quadrupole mass spectrometer (UHPLC-MS/MS) was developed and optimised to quantify CsA in ocular tissues and fluids. The CsA ocular kinetics in lachrymal fluid for both formulations were found to be similar between 15 min and 48 h. The CsA ocular distribution study evidenced the ability of the prodrug formulation to penetrate into the eye, achieving therapeutically active CsA levels in tissues of both the anterior and posterior segments. In addition, the detailed analysis of the in vivo data using a bicompartmental model pointed out a higher bioavailability and lower elimination rate for CsA when it is generated from the prodrug than after direct application as an emulsion. The interesting in vivo properties displayed by the prodrug solution make it a safe and suitable option for the treatment of DED.

A filtering method to correct time-lapse 3D ERT data and improve imaging of natural aquifer dynamics

We have developed a processing methodology that allows crosshole ERT (electrical resistivity tomography) monitoring data to be used to derive temporal fluctuations of groundwater electrical resistivity and thereby characterize the dynamics of groundwater in a gravel aquifer as it is infiltrated by river water. Temporal variations of the raw ERT apparent-resistivity data were mainly sensitive to the resistivity (salinity), temperature and height of the groundwater, with the relative contributions of these effects depending on the time and the electrode configuration. To resolve the changes in groundwater resistivity, we first expressed fluctuations of temperature-detrended apparent-resistivity data as linear superpositions of (i) time series of riverwater-resistivity variations convolved with suitable filter functions and (ii) linear and quadratic representations of river-water-height variations multiplied by appropriate sensitivity factors; river-water height was determined to be a reliable proxy for groundwater height. Individual filter functions and sensitivity factors were obtained for each electrode configuration via deconvolution using a one month calibration period and then the predicted contributions related to changes in water height were removed prior to inversion of the temperature-detrended apparent-resistivity data. Applications of the filter functions and sensitivity factors accurately predicted the apparent-resistivity variations (the correlation coefficient was 0.98). Furthermore, the filtered ERT monitoring data and resultant time-lapse resistivity models correlated closely with independently measured groundwater electrical resistivity monitoring data and only weakly with the groundwater-height fluctuations. The inversion results based on the filtered ERT data also showed significantly less inversion artefacts than the raw data inversions. We observed resistivity increases of up to 10% and the arrival time peaks in the time-lapse resistivity models matched those in the groundwater resistivity monitoring data.

One minute of grief: Emotional processing in short-term dynamic psychotherapy for adjustment disorder.

OBJECTIVE: Depth of emotional processing has shown to be related to outcome across approaches to psychotherapy. Moreover, a specific emotional sequence has been postulated and tested in several studies on experiential psychotherapy (Pascual-Leone & Greenberg, 2007). This process-outcome study aims at reproducing the sequential model of emotional processing in psychodynamic psychotherapy for adjustment disorder and linking these variables with ultimate therapeutic outcome. METHOD: In this study, 32 patients underwent short-term dynamic psychotherapy. On the basis of reliable clinical change statistics, a subgroup (n = 16) presented with good outcome and another subgroup (n = 16) had a poor outcome in the end of treatment. The strongest alliance session of each case was rated using the observer-rated system Classification of Affective Meaning States. Reliability coefficients for the measure were excellent (κ = .82). RESULTS: Using 1 min as the fine-grained unit of analysis, results showed that the experience of fundamentally adaptive grief was more common in the in-session process of patients with good outcome, compared with those with poor outcomes (χ2 = 6.56, p = .01, d = 1.23). This variable alone predicted 19% of the change in depressive symptoms as measured by the Beck Depression Inventory at the end of treatment. Moreover, sequences of the original model were supported and related to outcome. CONCLUSIONS: These results are discussed within the framework of the sequential model of emotional processing and its possible relevance for psychodynamic psychotherapy. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

A post-processing pipeline to reconstruct the developing fetal brain using low-resolution MRI

Introduction. Development of the fetal brain surfacewith concomitant gyrification is one of the majormaturational processes of the human brain. Firstdelineated by postmortem studies or by ultrasound, MRIhas recently become a powerful tool for studying in vivothe structural correlates of brain maturation. However,the quantitative measurement of fetal brain developmentis a major challenge because of the movement of the fetusinside the amniotic cavity, the poor spatial resolution,the partial volume effect and the changing appearance ofthe developing brain. Today extensive efforts are made todeal with the âeurooepost-acquisitionâeuro reconstruction ofhigh-resolution 3D fetal volumes based on severalacquisitions with lower resolution (Rousseau, F., 2006;Jiang, S., 2007). We here propose a framework devoted tothe segmentation of the basal ganglia, the gray-whitetissue segmentation, and in turn the 3D corticalreconstruction of the fetal brain. Method. Prenatal MRimaging was performed with a 1-T system (GE MedicalSystems, Milwaukee) using single shot fast spin echo(ssFSE) sequences in fetuses aged from 29 to 32gestational weeks (slice thickness 5.4mm, in planespatial resolution 1.09mm). For each fetus, 6 axialvolumes shifted by 1 mm were acquired (about 1 min pervolume). First, each volume is manually segmented toextract fetal brain from surrounding fetal and maternaltissues. Inhomogeneity intensity correction and linearintensity normalization are then performed. A highspatial resolution image of isotropic voxel size of 1.09mm is created for each fetus as previously published byothers (Rousseau, F., 2006). B-splines are used for thescattered data interpolation (Lee, 1997). Then, basalganglia segmentation is performed on this superreconstructed volume using active contour framework witha Level Set implementation (Bach Cuadra, M., 2010). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed (Bach Cuadra, M., 2009). Theresulting white matter image is then binarized andfurther given as an input in the Freesurfer software(http://surfer.nmr.mgh.harvard.edu/) to provide accuratethree-dimensional reconstructions of the fetal brain.Results. High-resolution images of the cerebral fetalbrain, as obtained from the low-resolution acquired MRI,are presented for 4 subjects of age ranging from 29 to 32GA. An example is depicted in Figure 1. Accuracy in theautomated basal ganglia segmentation is compared withmanual segmentation using measurement of Dice similarity(DSI), with values above 0.7 considering to be a verygood agreement. In our sample we observed DSI valuesbetween 0.785 and 0.856. We further show the results ofgray-white matter segmentation overlaid on thehigh-resolution gray-scale images. The results arevisually checked for accuracy using the same principlesas commonly accepted in adult neuroimaging. Preliminary3D cortical reconstructions of the fetal brain are shownin Figure 2. Conclusion. We hereby present a completepipeline for the automated extraction of accuratethree-dimensional cortical surface of the fetal brain.These results are preliminary but promising, with theultimate goal to provide âeurooemovieâeuro of the normal gyraldevelopment. In turn, a precise knowledge of the normalfetal brain development will allow the quantification ofsubtle and early but clinically relevant deviations.Moreover, a precise understanding of the gyraldevelopment process may help to build hypotheses tounderstand the pathogenesis of several neurodevelopmentalconditions in which gyrification have been shown to bealtered (e.g. schizophrenia, autismâeuro¦). References.Rousseau, F. (2006), 'Registration-Based Approach forReconstruction of High-Resolution In Utero Fetal MR Brainimages', IEEE Transactions on Medical Imaging, vol. 13,no. 9, pp. 1072-1081. Jiang, S. (2007), 'MRI of MovingSubjects Using Multislice Snapshot Images With VolumeReconstruction (SVR): Application to Fetal, Neonatal, andAdult Brain Studies', IEEE Transactions on MedicalImaging, vol. 26, no. 7, pp. 967-980. Lee, S. (1997),'Scattered data interpolation with multilevel B-splines',IEEE Transactions on Visualization and Computer Graphics,vol. 3, no. 3, pp. 228-244. Bach Cuadra, M. (2010),'Central and Cortical Gray Mater Segmentation of MagneticResonance Images of the Fetal Brain', ISMRM Conference.Bach Cuadra, M. (2009), 'Brain tissue segmentation offetal MR images', MICCAI.

Techniques for CT and MR, post-processing, radiation.

Brain perfusion can be assessed by CT and MR. For CT, two major techniquesare used. First, Xenon CT is an equilibrium technique based on a freely diffusibletracer. First pass of iodinated contrast injected intravenously is a second method,more widely available. Both methods are proven to be robust and quantitative,thanks to the linear relationship between contrast concentration and x-ray attenuation.For the CT methods, concern regarding x-ray doses delivered to the patientsneed to be addressed. MR is also able to assess brain perfusion using the firstpass of gadolinium based contrast agent injected intravenously. This method hasto be considered as a semi-quantitative because of the non linear relationshipbetween contrast concentration and MR signal changes. Arterial spin labelingis another MR method assessing brain perfusion without injection of contrast. Insuch case, the blood flow in the carotids is magnetically labelled by an externalradiofrequency pulse and observed during its first pass through the brain. Eachof this various CT and MR techniques have advantages and limits that will be illustratedand summarised.Learning Objectives:1. To understand and compare the different techniques for brain perfusionimaging.2. To learn about the methods of acquisition and post-processing of brainperfusion by first pass of contrast agent for CT and MR.3. To learn about non contrast MR methods (arterial spin labelling).

Organic matter processing and soil evolution in a braided river system

Traditionally, braided river research has considered flow, sediment transport processes and, recently, vegetation dynamics in relation to river morphodynamics. However, if considering the development of woody vegetated patches over a time scale of decades, we must consider the extent to which soil forming processes, particularly related to soil organic matter, impact the alluvial geomorphic-vegetation system. Here we quantify the soil organic matter processing (humification) that occurs on young alluvial landforms. We sampled different geomorphic units, ranging from the active river channel to established river terraces in a braided river system. For each geomorphic unit, soil pits were used to sample sediment/soil layers that were analysed in terms of grain size (<2mm) and organic matter quantity and quality (RockEval method). A principal components analysis was used to identify patterns in the dataset. Results suggest that during the succession from bare river gravels to a terrace soil, there is a transition from small amounts of external organic matter supply provided by sedimentation processes (e.g. organic matter transported in suspension and deposited on bars), to large amounts of autogenic in situ organic matter production due to plant colonisation. This appears to change the time scale and pathways of alluvial succession (bio-geomorphic succession). However, this process is complicated by: the ongoing possibility of local sedimentation, which can serve to isolate surface layers via aggradation from the exogenic supply; and erosion which tends to create fresh deposits upon which organic matter processing must re-start. The result is a complex pattern of organic matter states as well as a general lack of any clear chronosequence within the active river corridor. This state reflects the continual battle between deposition events that can isolate organic matter from the surface, erosion events that can destroy accumulating organic matter and the early ecosystem processes necessary to assist the co-evolution of soil and vegetation. A key question emerges over the extent to which the fresh organic matter deposited in the active zone is capable of significantly transforming the local geochemical environment sufficiently to accelerate soil development.

In vivo brain macromolecule signals in healthy and glioblastoma mouse models: (1) H magnetic resonance spectroscopy, post-processing and metabolite quantification at 14.1 T.

In (1) H magnetic resonance spectroscopy, macromolecule signals underlay metabolite signals, and knowing their contribution is necessary for reliable metabolite quantification. When macromolecule signals are measured using an inversion-recovery pulse sequence, special care needs to be taken to correctly remove residual metabolite signals to obtain a pure macromolecule spectrum. Furthermore, since a single spectrum is commonly used for quantification in multiple experiments, the impact of potential macromolecule signal variability, because of regional differences or pathologies, on metabolite quantification has to be assessed. In this study, we introduced a novel method to post-process measured macromolecule signals that offers a flexible and robust way of removing residual metabolite signals. This method was applied to investigate regional differences in the mouse brain macromolecule signals that may affect metabolite quantification when not taken into account. However, since no significant differences in metabolite quantification were detected, it was concluded that a single macromolecule spectrum can be generally used for the quantification of healthy mouse brain spectra. Alternatively, the study of a mouse model of human glioma showed several alterations of the macromolecule spectrum, including, but not limited to, increased mobile lipid signals, which had to be taken into account to avoid significant metabolite quantification errors.